[1]CHEN Wenbai,HUANG Zhicheng,LIU Qiong.A similar-face-image-retrieval system design based on a P-stable locality-sensitive Hashing algorithm[J].CAAI Transactions on Intelligent Systems,2017,12(3):392-396.[doi:10.11992/tis.201607005]
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A similar-face-image-retrieval system design based on a P-stable locality-sensitive Hashing algorithm

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 12 Number of periods: 2017 3 Page number: 392-396 Column: 学术论文—机器感知与模式识别 Public date: 2017-06-25
Title:
A similar-face-image-retrieval system design based on a P-stable locality-sensitive Hashing algorithm
Author(s):
CHEN Wenbai;  HUANG Zhicheng;  LIU Qiong
School of Automation, Beijing Information Science and Technology University, Beijing 100192, China
Keywords:
face-image retrieval; locality-sensitive Hashing algorithm; P-stable distribution; locally assembled binary feature
CLC:
TP18;TN911.22
DOI:
10.11992/tis.201607005
Abstract:
This paper proposes a similar-face-retrieval system based on a P-stable local hashing algorithm to meet the requirements of intelligent mobile terminals and mobile-robot-security inspection applications. First, our system extracts a locally assembled binary feature to detect a human face in a particular image. Subsequently, a deep auto-encoding network is used to compute the subject’s facial features. Finally, a locality-sensitive hashing algorithm based on a P-stable distribution is employed to construct an efficient index for each image according to the facial features. Our test results show that the proposed similar-face-image-retrieval system can process images within approximately 400 ms, thereby meeting the requirements of practical biometric applications. In addition, the false detection rate of the proposed method is considerably low than that of the classical AdaBoost algorithm.
References:
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